The CO2 record at the Amazon Tall Tower Observatory : A new opportunity to study processes on seasonal and inter-annual scales

High-quality atmospheric CO2 measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO2. In this study, we present the first 6 years (2014-2019) of continuous, high-precision measurements of atmospheric CO2 at the Amazon Tall Tower Observatory (ATTO, 2.1 degrees S, 58.9 degrees W). After subtracting the simulated background concentrations from our observational record, we define a CO2 regional signal (Delta CO2obs) that has a marked seasonal cycle with an amplitude of about 4 ppm. At both seasonal and inter-annual scales, we find differences in phase between Delta CO2obs and the local eddy covariance net ecosystem exchange (EC-NEE), which is interpreted as an indicator of a decoupling between local and non-local drivers of Delta CO2obs. In addition, we present how the 2015-2016 El Nino-induced drought was captured by our atmospheric record as a positive 2 sigma anomaly in both the wet and dry season of 2016. Furthermore, we analyzed the observed seasonal cycle and inter-annual variability of Delta CO2obs together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO2 exchange. We use both non-optimized and optimized (i.e., resulting from atmospheric inverse modeling) NEE fluxes as input in an atmospheric transport model (STILT). The observed shape and amplitude of the seasonal cycle was captured neither by the simulations using the optimized fluxes nor by those using the diagnostic Vegetation and Photosynthesis Respiration Model (VPRM). We show that including the contribution of CO2 from river evasion improves the simulated shape (not the magnitude) of the seasonal cycle when using a data-driven non-optimized NEE product (FLUXCOM). The simulated contribution from river evasion was found to be 25% of the seasonal cycle amplitude. Our study demonstrates the importance of the ATTO record to better understand the Amazon carbon cycle at various spatial and temporal scales.Peer reviewe

The CO2 record at the Amazon Tall Tower Observatory: A new opportunity to study processes on seasonal and inter-annual scales

Abstract High-quality atmospheric CO2 measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO2. In this study, we present the first 6 years (2014?2019) of continuous, high-precision measurements of atmospheric CO2 at the Amazon Tall Tower Observatory (ATTO, 2.1°S, 58.9°W). After subtracting the simulated background concentrations from our observational record, we define a CO2 regional signal () that has a marked seasonal cycle with an amplitude of about 4 ppm. At both seasonal and inter-annual scales, we find differences in phase between and the local eddy covariance net ecosystem exchange (EC-NEE), which is interpreted as an indicator of a decoupling between local and non-local drivers of . In addition, we present how the 2015?2016 El Niño-induced drought was captured by our atmospheric record as a positive 2σ anomaly in both the wet and dry season of 2016. Furthermore, we analyzed the observed seasonal cycle and inter-annual variability of together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO2 exchange. We use both non-optimized and optimized (i.e., resulting from atmospheric inverse modeling) NEE fluxes as input in an atmospheric transport model (STILT). The observed shape and amplitude of the seasonal cycle was captured neither by the simulations using the optimized fluxes nor by those using the diagnostic Vegetation and Photosynthesis Respiration Model (VPRM). We show that including the contribution of CO2 from river evasion improves the simulated shape (not the magnitude) of the seasonal cycle when using a data-driven non-optimized NEE product (FLUXCOM). The simulated contribution from river evasion was found to be 25% of the seasonal cycle amplitude. Our study demonstrates the importance of the ATTO record to better understand the Amazon carbon cycle at various spatial and temporal scales

Intra- and interannual changes in isoprene emission from central Amazonia

Isoprene emissions are a key component in biosphere-atmosphere interactions, and the most significant global source is the Amazon rainforest. However, intra- and interannual variations in biological and environmental factors that regulate isoprene emission from Amazonia are not well understood and, thereby, are poorly represented in models. Here, with datasets covering several years of measurements at the Amazon Tall Tower Observatory (ATTO) in central Amazonia, Brazil, we (1) quantified canopy profiles of isoprene mixing ratios across seasons of normal and anomalous years and related them to the main drivers of isoprene emission - solar radiation, temperature, and leaf phenology; (2) evaluated the effect of leaf age on the magnitude of the isoprene emission factor (Es) from different tree species and scaled up to canopy with intra- and interannual leaf age distribution derived by a phenocam; and (3) adapted the leaf age algorithm from the Model of Emissions of Gases and Aerosols from Nature (MEGAN) with observed changes in Es across leaf ages. Our results showed that the variability in isoprene mixing ratios was higher between seasons (max during the dry-to-wet transition seasons) than between years, with values from the extreme 2015 El Niño year not significantly higher than in normal years. In addition, model runs considering in situ observations of canopy Es and the modification on the leaf age algorithm with leaf-level observations of Es presented considerable improvements in the simulated isoprene flux. This shows that MEGAN estimates of isoprene emission can be improved when biological processes are mechanistically incorporated into the model.This research was supported by the German Federal Ministry of Education and Research, BMBF funds 01LB1001A; Brazilian Ministry of Science, Technology, Innovation and Communication; FINEP/MCTIC contract 01.11.01248.00); UEA; FAPEAM; LBA/INPA; and SDS/CEUC/RDS-Uatumã. It was also supported by grant nos. NSF-PRFB-1711997 and NSF-1754163. The article processing charges for this open-access publication were covered by the Max Planck Society.Peer reviewe

Comparison of Closed Chamber and Eddy Covariance Methods to Improve the Understanding of Methane Fluxes from Rice Paddy Fields in Japan

Greenhouse gas flux monitoring in ecosystems is mostly conducted by closed chamber and eddy covariance techniques. To determine the relevance of the two methods in rice paddy fields at different growing stages, closed chamber (CC) and eddy covariance (EC) methods were used to measure the methane (CH4) fluxes in a flooded rice paddy field. Intensive monitoring using the CC method was conducted at 30, 60 and 90 days after transplanting (DAT) and after harvest (AHV). An EC tower was installed at the centre of the experimental site to provide continuous measurements during the rice cropping season. The CC method resulted in CH4 flux averages that were 58%, 81%, 94% and 57% higher than those measured by the EC method at 30, 60 and 90 DAT and after harvest (AHV), respectively. A footprint analysis showed that the area covered by the EC method in this study included non-homogeneous land use types. The different strengths and weaknesses of the CC and EC methods can complement each other, and the use of both methods together leads to a better understanding of CH4 emissions from paddy fields.Peer Reviewe

Comparison of Closed Chamber and Eddy Covariance Methods to Improve the Understanding of Methane Fluxes from Rice Paddy Fields in Japan

Greenhouse gas flux monitoring in ecosystems is mostly conducted by closed chamber and eddy covariance techniques. To determine the relevance of the two methods in rice paddy fields at different growing stages, closed chamber (CC) and eddy covariance (EC) methods were used to measure the methane (CH4) fluxes in a flooded rice paddy field. Intensive monitoring using the CC method was conducted at 30, 60 and 90 days after transplanting (DAT) and after harvest (AHV). An EC tower was installed at the centre of the experimental site to provide continuous measurements during the rice cropping season. The CC method resulted in CH4 flux averages that were 58%, 81%, 94% and 57% higher than those measured by the EC method at 30, 60 and 90 DAT and after harvest (AHV), respectively. A footprint analysis showed that the area covered by the EC method in this study included non-homogeneous land use types. The different strengths and weaknesses of the CC and EC methods can complement each other, and the use of both methods together leads to a better understanding of CH4 emissions from paddy fields